Impact of COVID-19 fiscal measures on Non-Performing Loans

• Thesis title in Czech: Dopad fiskálních opatření COVID-19 na nesplácené úvěry
• Thesis title in English: Impact of COVID-19 fiscal measures on Non-Performing Loans
• English key words: non-performing loans, credit risk, fiscal measures, COVID-19 pandemic
• Academic year of topic announcement: 2020/2021
• Thesis type: Bachelor's thesis
• Thesis language: angličtina
• Department: Institute of Economic Studies (23-IES)
• Supervisor: doc. PhDr. Ing. et Ing. Petr Jakubík, Ph.D., Ph.D.
• Author: hidden - assigned by the advisor
• Date of registration: 26.09.2021
• Date of assignment: 26.09.2021
• Date and time of defence: 07.06.2022 09:00
• Venue of defence: Opletalova - Opletalova 26, O314, Opletalova - místn. č. 314
• Date of electronic submission: 03.05.2022
• Date of proceeded defence: 07.06.2022
• Opponents: Mgr. Nicolas Fanta

References

Ari, A., Chen, S. and Ratnovski, L. (2021). “The dynamics of non-performing loans during banking crises: A new database with post-COVID-19 implications“. In: Journal of Banking and Finance. url: https://doi.org/10.1016/j.jbankfin.2021.106140.

Balgova, M., Plekhanov, A. and Skrzypinska, M. (2017). “Reducing non-performing loans: stylized facts and economic impact“. Available at: https://www.ebrd.com/documents/admin/reducing-nonperforming-loans-stylized-facts-and-economic-impact.pdf?blobnocache=true.

Beck, R., Jakubík, P. and Piloiu, A. (2013). “Non-performing loans – What matters in addition to the economic cycle?“ In: Working Paper Series No. 1515. Macroprudential Reseaarch Network, ISSN 1725-2806 (online), European Central Bank. url: https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1515.pdf.

EBA. “Risk Assessment of the European Banking System“ December 2020. https://www.eba.europa.eu/sites/default/documents/files/document_library/Risk%20Analysis%20and%20Data/Risk%20Assessment%20Reports/2020/December%202020/961060/Risk%20Assessment_Report_December_2020.pdf. 24 September 2021

ECB. “What are non-performing loans (NPLs)? “ September 2016. https://www.bankingsupervision.europa.eu/about/ssmexplained/html/npl.en.html. 18 June 2021

Jakubík, P. and Reininger, T. (2014). “What Are the Key Determinants of Non-Performing Loans in CESEE?“ In: IES Working Paper 24. url: https://ideas.repec.org/p/fau/wpaper/wp2014_26.html.

Klein, N. (2013). “Non-Performing Loans in CESEE: Determinants and Impact on Macroeconomic Performance”. In: IMF Working Paper 72. url: https://www.imf.org/external/pubs/ft/wp/2013/wp1372.pdf.

Preliminary scope of work in English

Research question and motivation
The thesis aims to investigate to which extend fiscal measures related to COVID-19 have mitigated credit risk in selected European countries.

Among other indicators, the level of non-performing loans (NPLs) can be used to approximate and measure credit risk in the banking sector. According to the European Central Bank, a loan becomes non-performing when it is unlikely to be repaid by the borrower or if 90 or more days have passed since the due repayment date (ECB, 2021). Paying attention to NPLs is crucial as credit risk increases when loans are not paid back. This endangers banks' ability to grant new loans posing potential threat to the economy. As of June 2020, the credit risk accounted for 84% of risk-weighted assets in the European banks making it the largest banking risk (EBA, 2020).

Klein (2013) studied industry-specific and macroeconomic determinants of NPLs in Central, Eastern and Southeastern Europe (CESEE). The study states that for selected CESEE countries GDP growth, unemployment rate and inflation rate were suggested to be the causes of high levels of NPLs. The banks' indicators were significant too but not as much as the macroeconomic indicators. In a similar study by Jakubík and Reininger (2014), only macroeconomic variables were tested. It was confirmed that the real GDP growth is the main driver of the NPL ratio. Factors such as past credit growth, stock prices and exchange rate were shown to have explanatory power as well. Hence such variables can be essential in determining the NPL ratio. Having NPLs in a ratio to total number of loans takes into account volume differences and provides a comparable tool to measure credit risk. The reversed relationship between the NPL ratio and its determinants has been observed, too, hinting that an increase of the NPL ratio has negative effect on credit growth, inflation, and real GDP growth but positive effect on unemployment rate (Klein, 2013).

In 2017, Balgova et. al studied effectiveness of financial sector policies that aimed at reducing the NPLs. Out of five types of policies considered a combination of asset management companies and public funds for recapitalization were more successful at combating the NPLs. However, non-financial sector policies were not included which left the policies suited for borrowers behind. The paper from Ari et. al (2021) analyzes NPL dynamics during past banking crises and outlines potential adverse implications for the era after COVID-19. They show evidence that fast response to resolve NPLs is important for economic recovery. This proves that addressing the level of non-performing loans is necessary. Therefore, the aim is to find out which measures undertaken so far have been proved to be effective in resolving NPLs during the COVID-19 pandemic. Moreover, NPLs could potentially increase when the introduced measures will phase out. Hence, the aim is also to assess this risk.

Contribution
One of the most common issues, which is adressed in academic literature, is a set of determinants of NPLs as well as implications of NPLs on the economy. These issues are tackled mostly at country level and further granularity is missing. Research is also very limited when it comes to analyzing NPLs in the context of COVID-19 pandemic. This thesis could fill these two gaps and support further examination of related issues. As mentioned before, various policy packages were effective in resolving the NPLs but as Ari et. al (2021) showed, when measures are not adopted quickly, it slows down economic recovery. Therefore, another research aim is to discuss effectivness of fiscal measures, which can be used for better policy making decisions in practice. Morover, this study could estimate potential future negative effect on credit risk once the introduced fiscal measure will phase out.

Methodology
I will use time series data on non-performing loans segmented by economic sectors for individual countries in the European Union gathered and published by either national or European authorities. As the aim is to find effects of fiscal measures on the NPL ratio, I will also use fiscal measures related to COVID-19 that are available online. Information on these measures are regularly updated by European Systemic Risk Board. I will conduct panel data analysis applying regression models and perform robustness checks. Furthemore, I will also incorporate relevant control variables, selected macroeconomic indicators, that have been shown significant in explaining the NPL ratio to ensure that the effect of fiscal policies is measured. My goal is to find the relationship between fiscal measures adopted in response to COVID-19 and the NPL ratio.

Outline
1. Introduction
2. Literature Review
3. Theoretical Part
a) Non-Performing Loans – determinants and effects
b) COVID-19 – effects and fiscal responses
4. Empirical Part
a) Research methodology
b) Analysis of data
5. Results – interpretation and discussion
6. Conclusion